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Understanding how both the mean (location) and variance (scale) of traits differ among species and lineages is fundamental to unveiling macroevolutionary patterns. Yet, traditional phylogenetic comparative methods primarily focus on modelling mean trait values, often overlooking variability and heteroscedasticity that can provide critical insights into evolutionary dynamics. Here, we introduce phylogenetic location–scale models (PLSMs), a novel framework that jointly analyses the evolution of trait means and variances. This dual approach captures heteroscedasticity and evolutionary changes in trait variability, allowing for the detection of clades with differing variances and revealing patterns of adaptation, diversification, and evolutionary constraints. Extending PLSMs to a multivariate context enables simultaneous analysis of multiple traits and their covariances, facilitating the testing of hypotheses about evolutionary trade‐offs, pleiotropy and phenotypic integration. By modelling covariances between phylogenetic effects in both the location and scale parts, we can discern whether changes in one trait's mean or variance are associated with changes in another's, thereby offering deeper insights into the mechanisms driving trait co‐evolution and co‐divergence or ‘contra‐divergence’. We also describe how an extended version of PLSMs incorporating within‐species variability can enhance our understanding of trait convergence and divergence arising from ecological and environmental factors. Our framework provides a powerful tool for exploring macroevolutionary patterns and can be used to reassess previously published comparative data, offering new insights into the mechanisms driving the diversity of life.

Biological communities are structured phylogenetically—closely related species are typically more likely to be found at the same sites. This may be, in part, because they respond similarly to environmental gradients. Accurately surveying biological communities is, however, made difficult by the fact that detection of species is not perfect. In recent years, numerous statistical methods have been developed that aim to overcome deficiencies in the species detection process. However, these methods do not allow investigators to assess phylogenetic community structure. Here, we introduce the phylogenetic occupancy model (POM), which accounts for imperfect species detection while assessing phylogenetic patterns in community structure. Using simulated data sets we show that the POM grants less biased estimates of phylogenetic structure than models without imperfect detection, and can correctly ascertain the effects of species traits on community composition while accounting for evolutionary non-independence of taxa. Integrating phylogenetic methods into widely used occupancy models will help clarify how evolutionary history influences modern day communities.

Montane oceanic islands possess unique geographic and ecological attributes, rendering them valuable for assessing patterns and drivers of alpha and beta taxonomic, functional, and phylogenetic diversity along elevational gradients. Such comparisons of diversity facets can provide insights into the mechanisms governing community assembly on islands. Herein, we aimed to characterize taxonomic, functional, and phylogenetic bryophyte diversity on Madeira Island within and across areas at varying elevations. We also assessed how these diversity facets for the alpha and beta components relate to ecological and anthropogenic factors. We estimated and compared alpha and beta taxonomic, functional, and phylogenetic diversity using 80 plots of 0.5 m × 0.5 m across the whole elevational gradient of the island. We compiled trait databases and supplemented them with our own observations. Phylogenetic information was sourced from the Moss and Liverwort Tree of Life. To assess the impact of ecological and anthropogenic factors on the three facets, we applied linear mixed‐effects models and generalized dissimilarity models to alpha‐ and beta‐diversity matrices, respectively. All facets of diversity exhibited strong correlations within both mosses and liverworts, indicating a substantial congruence when alpha and beta are analyzed separately. The bryophyte groups categorized by the growth form demonstrated contrasting patterns, aligning with their distinctive ecological requirements. While a mid‐elevation peak emerged as a common pattern across the three facets of alpha diversity, beta diversity often displayed the opposite trend. Although the relative influence of environmental factors varied depending on the diversity facet and bryophyte grouping considered, we found that alpha and beta diversity of bryophytes are more influenced by climatic factors and the predominant type of vegetation than by anthropogenic factors. In the current context of global change, these results should be interpreted with caution, but they point to the resilience of bryophytes to survive in relatively well‐preserved natural microhabitats within anthropogenic landscapes. In this study on Madeira Island, we investigated patterns and drivers of alpha and beta taxonomic, functional, and phylogenetic diversity along elevational gradients. We found that alpha and beta diversity of bryophytes are more strongly influenced by climatic factors and the predominant type of vegetation than by anthropogenic factors. In this study on Madeira Island, we investigated patterns and drivers of alpha and beta taxonomic, functional, and phylogenetic diversity along elevational gradients. We found that alpha and beta diversity of bryophytes are more strongly influenced by climatic factors and the predominant type of vegetation than by anthropogenic factors.

Rapid losses and degradation of natural habitats in the tropics are driving catastrophic declines and extinctions of native biotas, including angiosperms. Determining the ecological and life-history correlates of extinction proneness in tropical plant species may help reveal the mechanisms underlying their responses to habitat disturbance, and assist in the pre-emptive identification of species at risk from extinction. We determined the predictors of extinction proneness in 1884 locally extinct (n = 454) and extant (n = 1430) terrestrial angiosperms (belonging to 43 orders, 133 families, and 689 genera) in the tropical island nation of Singapore (699.4 km²), which has lost 99.6% of its primary lowland evergreen rainforest since 1819. A wide variety of traits such as geographical distribution, pollination system, sexual system, habit, habitat, height, fruit/seed dispersal mechanism, and capacity for vegetative re-sprouting were used in the analysis. Despite controlling for phylogeny (as approximated by family level classification), we found that only a small percentage of the variation in the extinction probability could be explained by these factors. Epiphytic, monoecious, and hermaphroditic species and those restricted to inland forests have higher probabilities of extinction. Species dependent on mammal pollinators also probably have higher extinction probabilities. More comparative studies that use species traits to identify extinction-prone plant species are needed to guide the enormous, but essential task of identifying species most in need of conservation action.